merge develop into feat/freqai-rl-dev

tests/strategy/strats/strategy_test_v3_custom_entry_price.py

@@ -0,0 +1,37 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+from datetime import datetime
+from typing import Optional
+
+from pandas import DataFrame
+from strategy_test_v3 import StrategyTestV3
+
+
+class StrategyTestV3CustomEntryPrice(StrategyTestV3):
+    """
+    Strategy used by tests freqtrade bot.
+    Please do not modify this strategy, it's  intended for internal use only.
+    Please look at the SampleStrategy in the user_data/strategy directory
+    or strategy repository https://github.com/freqtrade/freqtrade-strategies
+    for samples and inspiration.
+    """
+    new_entry_price: float = 0.001
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        dataframe.loc[
+            dataframe['volume'] > 0,
+            'enter_long'] = 1
+
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return dataframe
+
+    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
+                           entry_tag: Optional[str], side: str, **kwargs) -> float:
+
+        return self.new_entry_price

tests/strategy/test_strategy_helpers.py

@@ -5,29 +5,8 @@ import pytest
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.enums import CandleType
 from freqtrade.resolvers.strategy_resolver import StrategyResolver
-from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
-                                timeframe_to_minutes)
-from tests.conftest import get_patched_exchange
-
-
-def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
-    np.random.seed(42)
-    tf_mins = timeframe_to_minutes(timeframe)
-
-    base = np.random.normal(20, 2, size=size)
-
-    date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
-    df = pd.DataFrame({
-        'date': date,
-        'open': base,
-        'high': base + np.random.normal(2, 1, size=size),
-        'low': base - np.random.normal(2, 1, size=size),
-        'close': base + np.random.normal(0, 1, size=size),
-        'volume': np.random.normal(200, size=size)
-    }
-    )
-    df = df.dropna()
-    return df
+from freqtrade.strategy import merge_informative_pair, stoploss_from_absolute, stoploss_from_open
+from tests.conftest import generate_test_data, get_patched_exchange
 
 
 def test_merge_informative_pair():

tests/strategy/test_strategy_loading.py

@@ -32,24 +32,25 @@ def test_search_strategy():
 
 def test_search_all_strategies_no_failed():
     directory = Path(__file__).parent / "strats"
-    strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
+    strategies = StrategyResolver._search_all_objects(directory, enum_failed=False)
     assert isinstance(strategies, list)
-    assert len(strategies) == 10
+    assert len(strategies) == 11
     assert isinstance(strategies[0], dict)
 
 
 def test_search_all_strategies_with_failed():
     directory = Path(__file__).parent / "strats"
-    strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
+    strategies = StrategyResolver._search_all_objects(directory, enum_failed=True)
     assert isinstance(strategies, list)
-    assert len(strategies) == 11
+    assert len(strategies) == 12
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 10
+    assert len([x for x in strategies if x['class'] is not None]) == 11
+
     assert len([x for x in strategies if x['class'] is None]) == 1
 
     directory = Path(__file__).parent / "strats_nonexistingdir"
-    strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
+    strategies = StrategyResolver._search_all_objects(directory, enum_failed=True)
     assert len(strategies) == 0
 
 
@@ -77,10 +78,9 @@ def test_load_strategy_base64(dataframe_1m, caplog, default_conf):
 
 
 def test_load_strategy_invalid_directory(caplog, default_conf):
-    default_conf['strategy'] = 'StrategyTestV3'
     extra_dir = Path.cwd() / 'some/path'
-    with pytest.raises(OperationalException):
-        StrategyResolver._load_strategy(CURRENT_TEST_STRATEGY, config=default_conf,
+    with pytest.raises(OperationalException, match=r"Impossible to load Strategy.*"):
+        StrategyResolver._load_strategy('StrategyTestV333', config=default_conf,
                                         extra_dir=extra_dir)
 
     assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog)
@@ -102,8 +102,8 @@ def test_load_strategy_noname(default_conf):
         StrategyResolver.load_strategy(default_conf)
 
 
-@pytest.mark.filterwarnings("ignore:deprecated")
-@pytest.mark.parametrize('strategy_name', ['StrategyTestV2'])
+@ pytest.mark.filterwarnings("ignore:deprecated")
+@ pytest.mark.parametrize('strategy_name', ['StrategyTestV2'])
 def test_strategy_pre_v3(dataframe_1m, default_conf, strategy_name):
     default_conf.update({'strategy': strategy_name})
 
@@ -349,7 +349,7 @@ def test_strategy_override_use_exit_profit_only(caplog, default_conf):
     assert log_has("Override strategy 'exit_profit_only' with value in config file: True.", caplog)
 
 
-@pytest.mark.filterwarnings("ignore:deprecated")
+@ pytest.mark.filterwarnings("ignore:deprecated")
 def test_missing_implements(default_conf, caplog):
 
     default_location = Path(__file__).parent / "strats"